reputation-engine

reputation-engine is an agent for Claude Code from vibeeval/vibecosystem. It costs 38 tokens per session (1,296 once invoked), scanned A, original, MIT.

An agent reliability scoring system that rates coding agents using their recent success, quality, consistency, and recovery history. It also tracks trust levels for assigning work.

In plain words
What is it for?
Use it to calculate agent reputation scores, recommend assignments, and monitor trust across a team.
Why use it?
It helps teams choose an agent for a task based on past results instead of guesswork. This can reduce risky assignments and show where an agent needs review or retraining.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: reads .claude/ paths.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/vibeeval/vibecosystem/reputation-engine
Clone the repo
git clone --depth 1 https://github.com/vibeeval/vibecosystem

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for reputation-engine

README.md
[![agentmods](https://agentmods.dev/badge/agents/vibeeval/vibecosystem/reputation-engine.svg)](https://agentmods.dev/agents/vibeeval/vibecosystem/reputation-engine)
Your own site
<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/reputation-engine"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/reputation-engine.svg" alt="Measured on agentmods" height="20"></a>
Per session 38 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,296 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.01296
Opus 5 $0.00019 $0.00648
Sonnet 5 $0.00008 $0.00259
Haiku 4.5 $0.00004 $0.00130

Measured 2d ago against content hash 2244b8abb81a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

reputation-engine scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/reputation-engine.md · 128 lines

How it starts

The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.

REPUTATION ENGINE — Agent Trust & Reliability Scoring

Domain: Agent Reliability Scoring | Assignment Optimization | Team Trust Index Data Source: ~/.claude/canavar/skill-matrix.json + ~/.claude/canavar/error-ledger.jsonl


SCORING MODEL

Agent Reputation Score (ARS) = 0-100

ARS = (success_rate * 0.35) + (first_pass_qa * 0.25) + (consistency * 0.20) + (recovery_speed * 0.20)

success_rate:     Basarili task / toplam task (son 30 gun)
first_pass_qa:    Ilk denemede QA gecen task orani
consistency:      Standart sapma tersi (tutarlilik)
recovery_speed:   FAIL sonrasi fix hizi (commit arasi sure)

Trust Tiers

Tier ARS Anlam Atama Politikasi
S-Tier 90-100 Elite Critical task'lar, tek basina calisabilir
A-Tier 75-89 Guvenilir Cogu task, minimal oversight
B-Tier 60-74 Orta Pair atama oner, review zorunlu
C-Tier 40-59 Riskli Sadece kucuk task, mentor eslik etsin
D-Tier 0-39 Sorunlu Yeniden egitim veya devre disi birak

CORE MODULES

1. Score Calculator (/reputation score )

# Canavar verilerini oku
SKILL_MATRIX="$HOME/.claude/canavar/skill-matrix.json"
ERROR_LEDGER="$HOME/.claude/canavar/error-ledger.jsonl"

Hesaplama adimlari:

  1. skill-matrix.json'dan agent profilini cek
  2. error-ledger.jsonl'den son 30 gun hatalarini filtrele
  3. QA loop retry sayilarini hesapla
  4. ARS formulu uygula
  5. Tier belirle

2. Assignment Advisor (/reputation suggest )

Task tipi verildiginde en uygun agent'i oner:

  • ARS skoru en yuksek agent'i sec
  • Task kategorisi ile agent uzmanligi eslestir
  • Son 7 gundeki workload'u kontrol et (burnout riski)
  • Ayni task tipinde gecmis performansi agirliklandir

Cikti formati:

TASK: API endpoint gelistirme
ONERILER:
  1. backend-dev (ARS: 87, A-Tier) — son 5 API task'ta 4/5 first-pass
  2. kraken (ARS: 82, A-Tier) — TDD ile daha yavas ama hatasiz
  3. spark (ARS: 71, B-Tier) — hizli ama review gerektiriyor
UYARI: frontend-dev bu task tipi icin uygun degil (ARS: 34 API task'larda)

Read the full file on GitHub · 128 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 128 lines · 38 tokens per session scan A 2244b8abb81a

Subscribe to this mod's changes

reputation-engine is an agent published in the GitHub repository vibeeval/vibecosystem (530 stars, last pushed 28d ago), licensed MIT. It adds 38 tokens to every session and 1,296 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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